This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. Primary support for the subproject and the subproject's principal investigator may have been provided by other sources, including other NIH sources. The Total Cost listed for the subproject likely represents the estimated amount of Center infrastructure utilized by the subproject, not direct funding provided by the NCRR grant to the subproject or subproject staff. Although late onset Alzheimer's disease (LOAD) is one of the most common neurodegenerative disorders its molecular etiology is far from being completely understood. In addition LOAD does not show any obvious inheritance pattern, complicating the diagnostics based on genetic background. To study the molecular mechanisms of the LOAD and potential links to the genetic background we have performed whole genome SNP genotyping using the Affymetrix 500K chips and transcriptome expression analysis using the Illumina ref-seq 8 chips on a series of 193 neuropathologically normal human brains and 177 samples from LOAD brains. So far we have analyzed and described the correlation of SNP polymorphism with gene expression profiles for brains from normal individuals and currently in the process of examining the LOAD series to look for DNA variants controlling RNA expression that might be involved in disease processes. However, it is very important to analyze this data in conjunction with protein abundance measurements, as the main molecular hallmark of Alzheimer's disease is the protein aggregation, which is pointing to dis-regulation of protein biosynthesis and degradation. The protein aggregates: senile plaques and neurofibrillary tangles predominantly consist of amyloid beta protein. However the recent LC-MS/MS proteomic profiling studies of senile plaques and neurofibrillary tangles obtained by laser capture microdissection have shown that those protein aggregates are more complex with estimated number of proteins ~25 and ~60, respectively. We propose for the current study to quantitatively analyze the human proteome with high throughput nano-LC FTICR MS in a limited subset normal and LOAD brains to investigate the potential links between genetic polymorphism, gene expression profiles, and protein abundance profiles with emphasis on protein aggregation. The quantitative proteome profiling is going to be a highly valuable addition to already collected data on genome and transcriptome profiling of normal and LOAD human brains.